S. Rappoccio
Impact in
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- Particle physics theoretical and experimental studies
- High-Energy Particle Collisions Research
- Quantum Chromodynamics and Particle Interactions
- Dark Matter and Cosmic Phenomena
- Particle Detector Development and Performance
- Astrophysics and Cosmic Phenomena
Papers in
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- Particle physics theoretical and experimental studies 4
- High-Energy Particle Collisions Research 4
- Particle Detector Development and Performance 3
- Dark Matter and Cosmic Phenomena 1
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- Computational Physics and Python Applications 1
- Explainable Artificial Intelligence (XAI) 1
- Machine Learning and Data Classification 1
- Co-authors
- Ulrich S. Schubert (1 shared paper)Christine Mclean (1 shared paper)L. Hay (1 shared paper)Garvita Agarwal (1 shared paper)I. Iashvili (1 shared paper)Margaret E. Morris (1 shared paper)L. Lista (1 shared paper)V. Adler (1 shared paper)
- Journals
- Journal of Physics Conference Series (1 paper)CERN Document Server (European Organization for Nuclear Research) (1 paper)AIP conference proceedings (1 paper)arXiv (Cornell University) (2 papers)
- Partner nations
- United StatesAustriaSwitzerland
In The Last Decade
S. Rappoccio
5 papers receiving 54 citations
Peers
Comparison fields: 5 of 18
- Nuclear and High Energy Physics 45
- Information Systems and Management 4
- Astronomy and Astrophysics 8
- Artificial Intelligence 11
- Computer Networks and Communications 7
Countries citing papers authored by S. Rappoccio
This map shows the geographic impact of S. Rappoccio's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by S. Rappoccio with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. Rappoccio more than expected).
Fields of papers citing papers by S. Rappoccio
This network shows the impact of papers produced by S. Rappoccio. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by S. Rappoccio. The network helps show where S. Rappoccio may publish in the future.
Co-authors
The 16 scholars most cited alongside S. Rappoccio, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 29 | |
| 2 | 2020 | 12 | |
| 3 | 2010 | 9 | |
| 4 | 2010 | 3 | |
| 5 | 2012 | 1 | |
| 6 | A new top jet tagging algorithm for highly boosted top jets | 2009 | 0 |
About S. Rappoccio
S. Rappoccio is a scholar working on Nuclear and High Energy Physics, Artificial Intelligence, Ocean Engineering, Infectious Diseases and Organic Chemistry, having authored 6 papers that have together received 54 indexed citations. Recurring topics across this work include Particle physics theoretical and experimental studies (4 papers), High-Energy Particle Collisions Research (4 papers), Particle Detector Development and Performance (3 papers), Reservoir Engineering and Simulation Methods (1 paper), Dark Matter and Cosmic Phenomena (1 paper), Computational Physics and Python Applications (1 paper), Explainable Artificial Intelligence (XAI) (1 paper) and Machine Learning and Data Classification (1 paper). The work is most often cited by research in Nuclear and High Energy Physics (45 citations), Information Systems and Management (4 citations), Astronomy and Astrophysics (8 citations), Artificial Intelligence (11 citations) and Computer Networks and Communications (7 citations). S. Rappoccio has collaborated with scholars based in United States, Austria and Switzerland. Frequent co-authors include Ulrich S. Schubert, Christine Mclean, L. Hay, Garvita Agarwal, I. Iashvili, Margaret E. Morris, L. Lista, V. Adler, R. Tenchini and R. Wolf. Their work appears in journals such as Journal of Physics Conference Series, CERN Document Server (European Organization for Nuclear Research), AIP conference proceedings and arXiv (Cornell University).
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.